1. Technical Field
The invention is related to video conferencing, and in particular, to a system and method for very low frame rate video streaming for face-to-face videoconferencing that employs novel eye tracking and blink detection techniques, as well as using image cropping and morphing to reduce frame rates.
2. Related Art
Face-to-face video communication is a potentially important component of real time communication systems. Inexpensive cameras connected to devices ranging from desktop computers to cell phones enable video conferencing in a variety of modes such as one-to-one and multi-party conferences.
Most video teleconference solutions are specifically designed for broadband networks and cannot be applied to low bandwidth networks. Previous face video compression techniques are not able to efficiently operate at very low bit rates because they compress and transmit the entirety of every video frame. Thus, reducing the bandwidth will of necessity degrade the image in every frame. There is a minimum for the allocated bits for each frame below which conventional compression techniques cannot produce visually acceptable results. Multi-party video conferences put an added strain on bandwidth requirements since multiple video streams need to be simultaneously transmitted in order for all of the participants to participate.
Different approaches have been proposed to reduce the bandwidth requirements for streaming video, such as the MPEG-4 face animation standard and H.26x video coding [1]. By taking advantage of face models, the MPEG-4 face animation standard can achieve a high compression ratio by sending only face model parameters. However, it is difficult to make the synthesized faces look natural and match the original video. H.26x waveform-based coding techniques are fully automatic and robust, but are not efficient for low bit-rate face video since their generality does not take advantage of any face models. These two types of techniques are combined together in a recently proposed low bit-rate face video streaming system [2], where prior knowledge about faces are incorporated into traditional waveform-based compression techniques to achieve better compression performance. This system is, however, not able to operate efficiently at very low bit rates (e.g., on the order of 8 kb/s).
Therefore, what is needed is a system and method that can provide face-to-face video conferencing at very low bit rates with natural looking results. Additionally, this system and method should be able to provide face-to-face video conferencing in real time.